Combinations of Tibetan tea and medicine food homology herbs: A new strategy for obesity prevention.
Food Sci Nutr
; 11(1): 504-515, 2023 Jan.
Article
em En
| MEDLINE
| ID: mdl-36655078
ABSTRACT
Obesity has become a significant global public health problem. Functional drinks have been an essential direction for obesity prevention research. The present study investigated the preventive effect and safety of winter melon and lotus leaf Tibetan tea (WLTT, a compound tea drink based on Ya'an Tibetan Tea and medicine food homology herbs) on obesity. The rats' hypercaloric high-fat diet (HFD) obesity model was established to evaluate obesity prevention and explored the mechanism through intestinal flora regulation. The results showed that in obese rats with the intervention of WLTT (400, 800, and 1600 mg/kg BW), the body weight, fat accumulation, adipocyte cell size, serum lipid levels, and antioxidant enzyme activity (SOD, GSH-Px, and MDA) were progressively improved. 16S rRNA high-throughput sequencing showed that WLTT could improve intestinal flora disorders due to HFD, which significantly reversed the relative abundance of Firmicutes and the F/B ratio associated with an HFD, and significantly upregulated the relative abundance of Verrucomicrobia. At the genus level, the downregulation of the relative abundance of Akkermansia and unclassified_Lachnospiraceae groups, and the upregulation of the relative abundance of Romboutsia, Ruminococcus, Corynebacteriume, and Saccharibacteria_genera_incertae_sedis groups brought about by the HFD were significantly reversed. The results of the above experiments were compared favorably with those of a parallel experiment with Bi -Sheng -Yuan slimming tea (BSY, a functional drink based on green tea and medicine food homology herbs). Overall, the findings have provided that WLTT can prevent obesity owing to an HFD by regulating intestinal flora and has a good safety profile, and combinations of Tibetan tea and medicine food homology herbs could be a new option for obesity prevention.
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Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Food Sci Nutr
Ano de publicação:
2023
Tipo de documento:
Article